Triple
T32639018
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | French Way |
E834428
|
entity |
| Predicate | hasTypicalAccommodationType |
P180876
|
FINISHED |
| Object | pilgrim hostels (albergues) |
—
|
LITERAL FINISHED |
How this triple was built (2 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: pilgrim hostels (albergues) | Statement: [French Way, hasTypicalAccommodationType, pilgrim hostels (albergues)]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasTypicalAccommodationType Context triple: [French Way, hasTypicalAccommodationType, pilgrim hostels (albergues)]
-
A.
hasTouristAccommodationType
chosen
Indicates that an entity provides or is classified by a specific type or category of tourist accommodation.
-
B.
hasAccommodation
Indicates that an entity provides, owns, or is associated with a place for someone to stay or live.
-
C.
hasHotelType
Indicates that a hotel is classified as belonging to a specific type or category (e.g., resort, boutique, hostel).
-
D.
accommodationStyle
Indicates the manner or type of lodging or housing arrangement provided or used in a given context.
-
E.
hasLodgeType
Indicates that an entity is associated with or classified by a particular type or category of lodge.
- F. None of above.
Provenance (3 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69f3492e773c81908afc10651e46cad3 |
completed | April 30, 2026, 12:21 p.m. |
| NER | Named-entity recognition | batch_69feced53a7c819098ec474fb7d514b0 |
completed | May 9, 2026, 6:06 a.m. |
| PD | Predicate disambiguation | batch_69fecd9cd5288190aac8b4e04a7ee78e |
completed | May 9, 2026, 6:01 a.m. |
Created at: May 1, 2026, 1:07 a.m.